An abstraction-guided simulation approach using Markov models for microprocessor verification

In order to combine the power of simulation-based and formal techniques, semi-formal methods have been widely explored. Among these methods, abstraction-guided simulation is a quite promising one. In this paper, we propose an abstraction-guided simulation approach aiming to cover hard-to-reach states in functional verification of microprocessors. A Markov model is constructed utilizing the high level functional specification, i.e. ISA. Such model integrates vector correlations. Furthermore, several strategies utilizing abstraction information are proposed as an effective guidance to the test generation. Experimental results on two complex microprocessors show that our approach is more efficient in covering hard-to-reach states than similar methods. Comparing with some work with other intelligent engines, our approach could guarantee higher hit ratio of target states without efficiency loss.